Xempla vs Clockworks Analytics: A Complete Comparison for Modern Maintenance Operations

With increasing pressure to enhance operational efficiency, reduce maintenance costs, and extend asset life cycles, Fault Detection and Diagnostics (FDD) software has become a key component of building operations technology. 

Two leading players in this space are Xempla and Clockworks Analytics, offering solutions designed to help FM Engineering teams optimize asset performance and proactively address issues before they become major disruptions. While both platforms provide best-in-class fault detection and diagnostics, they have fundamentally different approaches and philosophies, which is reflected clearly in how both products are built.

In this comprehensive guide, we’ll break down the core differences between Xempla and Clockworks Analytics — what they do well, where they fall short, ideal use cases they’re best suited for, and how to decide which one makes more sense for you. No fluff, no marketing speak, just a real-world comparison that helps you make an informed choice.

Overview of Xempla and Clockworks Analytics

Before we dive into the differences, let’s set the stage with a brief introduction of Xempla and Clockworks Analytics. What exactly do Xempla and Clockworks Analytics do?

What is Xempla?

Xempla is built as an autonomous maintenance and decision intelligence platform. It’s not just about detecting faults, it’s about making sure those faults get fixed without drowning your team in unnecessary alerts. Instead of just throwing raw data and basic diagnostics at engineers, Xempla analyzes, triages, and automates corrective actions, so they can focus on what matters.

The idea here is less manual effort, fewer distractions, and more reliable operations. Xempla integrates fault detection and diagnostics with your maintenance workflows, meaning it can prioritize issues, generate work orders, and even help standardize best practices across different sites. Think of it as an AI Reliability Engineer who handles critical tasks autonomously and a 24/7 assistant who works with your team, providing all the insights and information they need to drive better and faster decisions for enhanced asset performance, reliability, and maintenance efficiency over time.

What is Clockworks Analytics?

Clockworks Analytics takes a different approach. It’s primarily a building analytics and fault detection diagnostics platform designed to give engineers and facility managers visibility and detailed insights into their building systems. If you’ve got a strong in-house engineering team that loves getting into the weeds of system performance, Clockworks is built for you.

It excels at fault detection, root cause analysis, and energy efficiency tracking. Unlike some of the more conventional FDD tools that just spit out alerts, Clockworks provides structured reports that explain faults in context, so engineers can diagnose and act accordingly. But here’s the catch — it doesn’t automate the fix. It’s a powerful tool, but you’ll need a team ready to interpret the data and manually decide what to do next.

Head-to-Head Comparison: Key Differences Between Xempla and Clockworks Analytics

Now that we’ve covered the basics, let’s get into the real differences. Both platforms help facility management teams detect and diagnose faults, but they take very different paths to get there and how they handle what happens beyond. Here's a breakdown of the key differences between Xempla and Clockworks across the most important factors:

1. Approach & Philosophy

The biggest difference between Xempla and Clockworks Analytics is their philosophy around fault detection and diagnostics and how it connects to overall maintenance workflows.

• Xempla treats FDD as a component of the broader operations and maintenance process and drives automation and decision intelligence. It’s designed to reduce the manual workload, providing better efficiency in routine tasks and shifting engineers to supervisory roles and oversight for critical decisions. The goal? Fewer distractions, more focus on fast and accurate fixes, and a shift toward autonomous maintenance.
  
• Clockworks Analytics is all about deep engineering analysis. It provides detailed reports and structured insights so engineers can manually diagnose issues and decide the best course of action. It’s built for teams that want complete control over their fault detection process and are comfortable making all the decisions themselves.

Bottom line: If you want a platform that automates fault detection, diagnostics, and routine decisions, Xempla is a better fit. If you prefer full control over fault analysis and decision-making, Clockworks might suit you better.

2. Fault Detection & Diagnostics Capabilities

How each platform identifies and reports faults is another big difference.

• Xempla uses AI-driven analytics and core engineering principles to detect faults and assess their impact before engineers take over. More importantly, it flags recurring issues while minimizing false alarms and one-off events. Along with specific insights, it automatically gathers context on the asset, runs risk / compliance assessments, and recommends corrective actions to help you make the best decision as quickly as possible.
  
• Clockworks uses rule-based analytics to detect faults and generate in-depth engineering reports. These reports provide a detailed breakdown of anomalies, possible causes, and performance inefficiencies. However, it’s up to the engineers to act on this data manually, look for vital context spread across other maintenance platforms (if available), and decide the next set of actions.

Bottom line: Xempla is better if you want automated fault detection, fewer false alarms, and critical context for better diagnostics and investigations. Clockworks is better if you want detailed reports and prefer to manage faults manually.

3. Automation & Work Order Integration

A fault detection and diagnostics system becomes exponentially more powerful if it closes the loop with work order management and effective implementation of corrective actions. This is where Xempla and Clockworks take two very different approaches.

• Xempla connects the FDD process with work order management and automates the next steps. Once the diagnosis and investigation stage begins, it assigns an overall confidence score and provides go / no-go recommendations for work order generation. With enough user-based learning, it can completely automate work orders with relevant instructions for technicians, helping in more effective interventions.
  
• Clockworks provides structured reports, but engineers must take manual action. While it integrates with CMMS and work order systems, it doesn’t automate the decision-making process. Engineers need to interpret the data, decide what’s important, and then create work orders themselves. There’s little to no system support in terms of whether a certain fault needs to be converted into a work order or not. 

Bottom line: If you want a system that automates corrective actions and integrates seamlessly into work orders, Xempla is the way to go. If you prefer a report-based system where engineers manually decide what becomes a work order, Clockworks is a strong choice.

4. Team Productivity & Workload

How do these platforms impact the daily work of engineers and technicians?

• Xempla reduces manual workload. Engineers don’t have to sift through endless alarms or manually triage issues. Xempla maximizes engineering time and skills, minimizes cognitive load, and streamlines workflows, allowing engineers to focus on high-value tasks​. AI takes care of routine decisions, letting them focus on complex problems and strategic maintenance planning. There’s also the added benefit of seamless digital communication and collaboration with technicians — all within the platform, without having to jump between different tools.
  
• Clockworks provides extensive data but demands more manual effort. If your engineers enjoy digging into detailed reports and manually deciding what to do next, this might be a good thing. While this level of detail can be beneficial for technically skilled teams, if you’re already stretched thin, Clockworks could add to your workload rather than reduce it. Additionally, since work orders and communication interfaces aren’t built into the platform, teams must use external systems, which can create friction in day-to-day workflows.

Bottom line: Xempla is ideal for organizations that want to run leaner operations, maximize efficiency, and do more with less/existing resources. Clockworks Analytics is better suited for organizations that follow a manual, resource-intensive maintenance model and have dedicated in-house teams that prefer hands-on diagnostics over automated workflows.

6. Knowledge Retention & Institutional Learning

How well does each platform help facility teams capture, retain, and reuse knowledge over time?

• Xempla builds an evolving knowledge base for long-term operational intelligence. Instead of starting from scratch every time a new fault occurs, it learns from past incidents and resolutions. Engineers and technicians can document learnings, share insights, and store best practices directly within the platform. Over time, this helps reduce reliance on individual expertise, ensuring that operational knowledge stays within the organization even as personnel change and new engineers quickly get up to speed.
  
• While Clockworks offers highly structured diagnostics and insights, it focuses on individual fault detection and resolution rather than long-term learning. Engineers receive detailed reports for each issue, but there’s no centralized system for capturing and reusing tribal knowledge. As a result, if key personnel leave, their expertise may not be easily transferred, potentially leading to knowledge gaps, increasing organizational risk, and reducing competitiveness over time.

Bottom line: If you want a system that captures institutional knowledge, builds a self-improving database of insights, and ensures long-term learning across teams, Xempla is the better choice. If your priority is highly detailed one-time diagnostics without a structured knowledge retention framework, Clockworks Analytics is a solid option.

6. Scalability & Industry Fit

Which industries and building types are best suited for each platform?

• Xempla is highly scalable and works well across all types of assets in the built environment — commercial real estate, healthcare, data centers, retail and residential facilities, solar plants, and more. It’s especially useful for multi-site operations where standardization, automation, and centralized decision-making are essential for efficiency and consistency.
  
• Clockworks Analytics is ideal for HVAC-centric diagnostics in large enterprise buildings. It excels in detailed fault detection and energy efficiency analysis, making it a strong fit for large commercial buildings, corporate campuses, and institutions with robust in-house engineering teams. However, because it relies heavily on manual interpretation of data, it’s better suited for single-site facilities or organizations that prioritize deep technical analysis over automated decision-making.

Bottom line: If you need a scalable solution for multiple sites and diverse assets, Xempla is a better fit. If you’re running a large facility with an in-house engineering team that prefers deep technical analysis, Clockworks might be the way to go.

7. Cost & Implementation Complexity

Without getting into specific pricing, here’s what you need to know:

• Xempla is designed for fast deployment with minimal friction. It integrates smoothly with existing systems, requires little to no customization, and doesn’t demand extensive training for teams to start using it effectively. The platform is intuitive and designed to deliver value quickly, ensuring that teams can adopt and benefit from AI-driven insights without a steep learning curve.
  
• Clockworks Analytics requires more setup and training. As a data-heavy platform with highly detailed diagnostics, unlocking its full potential requires proper configuration and training. Teams need to understand how to interpret reports, prioritize actions, and manually implement solutions, which can take time and resources. While powerful, the system’s complexity may pose challenges for organizations without dedicated in-house expertise.

Bottom line: If you need a solution that works quickly, integrates seamlessly, and doesn’t require extensive training, Xempla is the better option. If you have the time and resources to train your team on a highly detailed diagnostics platform, Clockworks is a strong choice.

Over to You: When to Choose Xempla vs When to Choose Clockworks Analytics

Both Xempla and Clockworks Analytics bring valuable capabilities to the table — but the right choice depends on what you need from your asset performance and maintenance strategy. Whether you’re a facility manager, an engineering leader, or a decision-maker evaluating FDD solutions, the right tool for you will ultimately depend on how you want to manage your buildings, what kind of team you have, and whether you’re looking to maximize the value of AI and automation for your organization.

• Clockworks Analytics is a diagnostics-first platform that focuses on generating in-depth engineering insights, helping FM teams analyze faults and inefficiencies in detail.
• Xempla, on the other hand, is an AI-driven autonomous maintenance and decision intelligence platform, designed to automate fault triaging, streamline workflows, and boost efficiency and resource utilization through proactive maintenance strategies.

If you’re looking for a deeply technical FDD platform that provides detailed engineering-level diagnostics, and you have the resources to manually analyze and act on the insights, Clockworks is a strong choice. It excels in HVAC system monitoring, making it ideal for organizations with dedicated in-house teams focused on system-level diagnostics.

However, Xempla goes beyond Fault Detection and Diagnostics software like Clockworks by operating as a System of Outcomes focused on improving asset performance, data-driven decision-making, and directly contributing to business efficiency and operational excellence​. It incorporates important use cases like condition-based maintenance and predictive maintenance, drives multi-site standardization, and helps teams focus on what matters most: execution and impact.

Therefore, Xempla’s AI-first, autonomous maintenance approach ensures that organizations move beyond reactive fault detection toward continuous optimization and proactive asset management​.

That’s all from us in this comparison. Now over to you.